The present invention relates to wireless communication systems, and more particularly to estimating the channel in such systems.
To decode symbols in an OFDM system, the channel response is often estimated in the frequency domain. To achieve this, pilot tones (pilot subcarriers), known to the receiver, are transmitted. The pilot tones are also used to estimate the channel for non-pilot tones that contain modulated data. A number of well known techniques such as polynomial interpolation, filtering such as minimum mean square error (MMSE) filter or Wiener filter, or Fast Fourier transform (FFT) may be used to estimate the channel. Because an OFDM system has an FFT block, there are obvious cost/space advantages in using the existing FFT block to estimate the channel.
FIG. 1 shows a number of blocks of a channel estimation system 100 that uses FFT to estimate the channel. Inverse FFT block 102 receives pilots S1 which have a higher density than the original pilots. A number of different interpolation techniques may be used to increase the density of pilots. Since pilots S1 are not located at all the subcarriers, images appear in the output S2 of inverse FFT block 102. Windowing and noise reduction block 104 is used to remove the images and reduce the noise present within the channel estimation window. The channel estimation window includes most of the channel energy. The noise may be reduced using any number of signal processing algorithms. Output signal S3 of windowing and noise reduction block 104 is applied to FFT block 106, which in turn provides an estimate of the channel S4 in frequency domain. The windowing and noise reduction performed by block 104 also causes loss of signal energy. This causes signal S4 to have a roll-off near the edges of the signal band, in turn causing performance degradation. To achieve better performance, the roll-off near the edges of the signal band needs to be compensated. The roll-off may be reduced by increasing the channel estimation window. However, increasing the channel estimation window may further degrade the performance.
FIG. 2 shows a channel estimation system 100 coupled to an MMSE filter 120. Signal S5 represents the pilot tones located near the edges of the signal band S1. MMSE filter 120 is adapted to use signal S5 to compensate for the roll-offs near the edges of the signal band. The channel estimates near the edges of signal S4 are replaced by the output signal S6 of MMSE filter 120. One disadvantage of MMSE filter 120 is that its filter coefficients vary when the channel changes. A need continues to exist for an improved method and system for estimating a communication channel.